{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a20facef0>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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3iIhIbtw3iBwdHfnf//1ffvnlFw4dOsSOHTsIDAykYcOGfPzxxyxdupStW7fyySefsHPn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\nUQoiEREx6v8Bd7rpIQQiBv0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a20fb4470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "#设置字体为中文字体的路径\n",
    "from matplotlib.font_manager import FontProperties\n",
    "font=FontProperties(fname='/Library/Fonts//Arial Unicode.ttf',size=10)\n",
    "\n",
    "\n",
    "df = sns.load_dataset('iris')\n",
    "\n",
    "\n",
    "sns.boxplot(x=df[\"sepal_length\"], y=df[\"species\"] );\n",
    "_ = plt.xlabel('花瓣长度 (cm)', fontproperties=font, fontsize=16)\n",
    "_ = plt.ylabel('物种', fontproperties=font, fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
